Simple Models to Estimate Historical and Recent Changes of TotalOrganic Carbon Concentrations in LakesSalar Valinia,*,† Martyn N. Futter,† Bernard J. Cosby,‡ Peter Rosen,§ and Jens Folster†

†Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Lennart Hjelms vag 9, SE-75007Uppsala, Sweden‡Center for Ecology and Hydrology, Environment Centre Wales, Deiniol Road, Bangor LL57 2UW, United Kingdom§Department of Ecology and Environmental Science, Umea University, SE-90187 Umea, Sweden

*S Supporting Information

ABSTRACT: Quantifying human impacts on the naturalenvironment requires credible reconstructions of referenceconditions. Anthropogenic acidification of surface waters isstrongly influenced by total organic carbon (TOC) concen-trations. Because both the degree of acidification and recoveryare dependent on historical TOC concentrations, simplemodels to estimate changes in surface water TOC betweenreference conditions (1860) and the present day (2012) areneeded. We used visible near infrared spectroscopy (VNIRS)of lake sediments to reconstruct reference condition TOC andlong-term monitoring data to predict recent changes. Twoempirical models were developed to predict: (i) historical TOC trends between reference conditions (1860) and peakacidification (1980) and (ii) trends in TOC between 1988 and 2012. The models were statistically robust with adj. R2 of (i) 0.85and (ii) 0.71, respectively. Models were driven by lake and catchment area, wetlands, historical sulfur deposition and waterchemistry. Present day TOC concentrations are similar to VNIRS-reconstructed and modeled reference condition TOC inSwedish lakes. The results are valuable for understanding drivers of TOC changes in lakes and for more credible assessments ofreference conditions needed for water management in Europe and elsewhere.

1.0. INTRODUCTION

Scientists and policy makers must understand the effects ofanthropogenic disturbance on water quality. Both the EUWater Framework Directive (WFD; 2000/60/EC) and U.S.Clean Water Act are based on the concepts of undisturbed stateand reference conditions. Reference conditions are conceptual-ized as the state that existed before the onset of major humaninfluence on the environment, and hence are assumed toapproximate an undisturbed state. Because observations neededto quantify the undisturbed state are often not available,reference conditions are ambiguous.1 In Europe, referenceconditions are defined as the state assumed to have existedprior to 1860, even though human activities had alreadysubstantially changed the environment by that time.2 The mostproblematic issue with the use of reference conditions formanagement purposes is that they cannot be observed directlyand their reconstruction is reliant on proxies such as sedimentrecords or mechanistic models. Any reconstruction of referenceconditions has associated uncertainties. Simple, credibleestimates of historical changes between reference conditionsand the present are nonetheless needed to reduce the predictiveuncertainties of more complex dynamic models. For instance,dynamic models are one of the methods used to reconstructreference condition water chemistry so as to assess the degreeof anthropogenic acidification of surface waters.3 Reconstruc-

tions of reference conditions for acidification assessment arevery sensitive to assumptions made about historical totalorganic carbon (TOC) concentrations.4,5 In this study, weshow how historical changes in lake water TOC concentrationscan be estimated on a regional scale to reduce the ambiguityassociated with reference conditions in surface waters.In Sweden, particulate organic carbon generally comprises a

very small fraction of TOC. Thus, all TOC measurementspresented here are effectively equivalent to dissolved organiccarbon (DOC),6,7 and all results will be presented as TOC.Concentrations of surface water DOC have been increasing

in many parts of Europe and North America during the threepast decades.8−13 Different hypotheses have been proposed toexplain this phenomenon. Both increasing atmosphericCO2

14,15 and global warming can increase terrestrial productionof organic matter with consequent increases in DOC leachingto surface water.16,17 Seasonality and hydrological events can bethe main drivers of short-term changes in TOC in streams andland management may also cause changes in surface waterDOC.18,19 Many studies have suggested that increases in

Received: June 30, 2014Revised: December 8, 2014Accepted: December 8, 2014Published: December 8, 2014

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surface water DOC are linked to declining levels of aciddeposition8,20,21 and subsequent recovery from acidification.22

Furthermore, studies have shown that the quality of dissolvedorganic matter (DOM) can change in response to aciddeposition.23,24 Although there is no single explanation forthe observed increase in DOC, it is clear that acid deposition,climate and land management are important controllingvariables. One key unanswered question is for how long willsurface water TOC concentrations increase and when, if ever,will they reach reference condition levels? This question is hardto address, as little is known about historical levels of DOCbecause monitoring data rarely extends far enough into the pastto analyze potential regional drivers on a long-term scale. Forexample, Swedish monitoring data for acid sensitive lakesextends approximately 30 years into the past,25 and a fewcontinuous records in Fennoscandia go back 50 years.17 This isusually not long enough to examine changes in water chemistryon a regional scale prior to major industrialization.26

A paleolimnological approach to reconstruct TOC overdecadal to millennial time scale is visible-near infraredspectroscopy (VNIRS-TOC).27−29 The VNIRS-TOC techni-que takes advantage of the complex signature of organic matterpreserved in lake sediments so as to reconstruct historical TOCconcentrations. The VNIRS-TOC method has been applied tomultiple lakes in the Northern Hemisphere in Sweden,27−30

Canada31 and European Russia.32 One of the main drawbacksof using sediment cores and the VNIRS-TOC technique is theamount of resources needed to produce a time series for onelake, rendering its use on a regional scale impractical. A simple,regional scale approach to estimate historical TOC based onVNIRS-TOC reconstructions in the lake rich boreal eco-zone isneeded. The development of a simple method to estimatehistorical reference condition lake water TOC concentrationssupports the goals of the WFD (Europe) and Clean Water Act(U.S.). Here, we develop (i) an empirical model based onVNIRS-TOC, sulfur deposition and catchment properties toassess the historical trend in TOC between 1860 and 1980 and

(ii) a second model to predict contemporary trends in TOCbetween 1988 and 2012 based on water chemistry andcatchment properties.

2.0. MATERIALS AND METHODS

2.1. Lake Water Parameters and Catchment Charac-teristics. This study included data from 110 lakes sampled inthe Swedish national and regional lake monitoring programs.25

The lakes were small to intermediate sized (Table 1) withminimal influence from point sources; hence, the water qualityis controlled primarily by climatic factors and long-range trans-boundary pollution. Samples for water chemistry were collectedfour times annually between 1988 and 2012; annual averageswere used in the study. The study lakes spanned the majorclimatic, physiographic, chemical and deposition gradientsacross Sweden (Figure 1, Table 1). VNIRS-TOC reconstruc-tions of historical TOC were available from 14 of those lakes.Catchment land use was obtained from the European CORINELand Cover database for the year 2000.33 Catchment areaswere log-transformed to achieve a more normal distribution ofvalues. The Swedish Meteorological and Hydrological Institute(SMHI) lake register was used for lake depths when available(http://www.smhi.se/klimatdata/hydrologi/sjoar-och-vattendrag), for the remainder of the lakes, depths werecalculated.34 Modeled long-term annual mean runoff 1990−2010 was obtained using the SMHI S-HYPE model (http://vattenweb.smhi.se). Gridded (50 × 50 km) reconstructions ofatmospheric sulfur deposition from 1880 to 2010 wereprovided by Coordination Centre for Effects (CCE).35 Sulfurdeposition (mg S m−2 yr−1) in 1980 was used as a proxy forpeak acidification in Sweden.

2.2. Visible Near Infrared Spectroscopy inferred TOC.The VNIRS-TOC method exploits the fact that organic matteris preserved in lake sediments. By characterizing the quality oforganic matter in the lake sediments, it is possible toreconstruct historical TOC concentrations because the complexstructure and distinctive VNIRS signature can be summarized

Table 1. Information of Lake Parameters Including in-Lake Chemistry, Catchment Coverage and Climate That Are Included inthe Study (n = 110) for the Year 2012

variable abbreviation mean ± std dev min max

in-lake chemistrytotal organic carbon (mg L−1) TOC 12 ± 6.3 0.8 36.5pH pH 6.2 ± 0.6 4.5 7.1sum Ca2+, Mg+, K+, Na+ (meq L−1) ΣBC 0.35 ± 0.14 0.06 0.8SO4

2− (meq L−1) 0.06 ± 0.04 0.009 0.2alkalinity (meq L−1) Alk 0.08 ± 0.07 −0.05 0.3total phosphorus (μg L−1) Tot-P 12.0 ± 8.2 1.25 41total nitrogen (μg L−1) Tot-N 56 ± 67 70 1320EMEP sulfur deposition 1980 (mg m−2 yr−1) sulfurEMEP 1980 1678 ± 758 368 2916catchment characteristicswater retention time (years) WRT 0.7 ± 1.1 0.5 10catchment area (km2) 17.4 ± 57.1 0.05 395lake area (km2) 1.4 ± 4.9 0.006 40water (% of catchment) % water 12 ± 7.2 1.2 30forest (% of catchment) % forest 71.2 ± 19.3 0 93wetland (% of catchment) % wetland 9.5 ± 10.5 0 64agriculture (% of catchment) % agriculture 1.2 ± 2.5 0 12climate variables (2010)mean annual air temperature (°C) T 4.6 ± 2.6 −3 7.5mean annual precipitation (m yr−1) P 0.94 ± 0.18 0.68 1.40runoff (m yr−1) Q 0.29 ± 0.06 0.15 0.44

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with multivariate statistics.29 Using partial least squares (PLS)regression, a model can be developed in which the VNIRSspectra of surface sediment and contemporary lake water TOCcan be summarized into a few orthogonal components.36 Thiscalibration model facilitates the calculation of historical lakewater TOC concentrations from VNIRS signatures of organicmatter in the sediments. The calibration model included 140Swedish lakes covering a TOC gradient between 0.7 mg and24.7 mg L−1, approximately half of the 140 lakes were in alpinecatchments above the tree-line and the rest were in forest(birch or pine) dominated catchments.27,29 The sediment coreswere collected using a Kajak corer during July−August 2006.Cores were collected from the deepest part of the lake andextruded in the field at either 0.5 or 1 cm resolution. The coreswere dated using Pb-210 γ-spectrometry.37 More informationon the VNIRS methodology and calibration sets is availableelsewhere.27,29 All sediment intervals (30 cm) of core has beenanalyzed with VNIRS at 0.5 or 1 cm resolution. Only thesediment depth back to 1860 or bottom sediment with Pb-210dating has been used in this study. The number of analysesdiffered due to sedimentation rates in the lake, the number ofanalyses for individual lakes ranged between 13 and 29 with amedian of 21.

2.3. Simple and Multiple Linear Regression Models.Stepwise multiple linear regression (MLR) was performed toestimate the slope of VNIRS-TOC concentrations between1860 and 1980 (n = 14) and slope in measured TOCconcentrations between 1988 and 2012 (n = 107). The twomodels were created independently. For each model, the firststep was to evaluate the most significant predictor variables forthe slopes from a set of candidate predictor variables (Table 2).Model goodness of fit was evaluated using the coefficient ofdetermination R2. A candidate parameter was accepted in theMLR model when it increased the R2-value by 0.01,38 and wassignificant in the stepwise regression (p < 0.05). To avoid

Figure 1.Map of Sweden with all lakes included in this study; trianglesrepresent lakes that have VNIRS inferred TOC (n = 14) and circlesrepresents lakes with long-term monitoring data from the Swedishnational monitoring program (n = 107).

Table 2. All Candidate Parameters Used in the Multiple Linear Regression (MLR) to Create the Different Modelsa

model

parameter 1860−1980 VNIRS 1988−2012 measured

physical parameters significance t-ratio significance t-ratio

lake area (km2) p = 0.0001 6.06 n.s.log catchment area (km2) p < 0.0001 −7.48 n.s.forest (%) of whole catchment n.s. n.s.mean annual Q (m yr−1) n.s. p = 0.0008 −3.48relative area (%) n.s. n.s.retention time (yr−1) n.s. n.s.wetland (%) of whole catchment n.s. p < 0.0001 −5.12lake volume (m3) n.s. n.s.chemical parameterspH not tested p < 0.0001 −9.98BC* (meq L−1) not tested p < 0.0001 7.05SO4

2−* (meq L−1) not tested p < 0.0001 −6.44EMEP sulfur deposition in 1980 (mg m−2 yr−1) p = 0.0009 −4.65 p = 0.0009 3.42Cl (meq L−1) not tested n.s.Tot-N (meq L−1) not tested n.s.climatic parametersprecipitation (m yr−1) n.s. n.s.mean annual temperature (°C) n.s. n.s.

aTwo criteria had to be fulfilled for the parameter to be included in the final model: p < 0.05 and improvement of adj. R2 of 0.01. Water chemicalparameters were not tested for the VNIRS model due to absence of measurements during this period. Specific significance numbers are given in thetable together with t-ratio from the models.

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spurious intercorrelation, the parameters in the model wereonly accepted in the final prediction when VIF (variableinflation factor, a measure of intercorrelation between thepredictors in the MLR) values were below 10. The modelpredictions were evaluated using the normalized root-mean-square error (NRMSE; NRMSE = RMSE/range). Parametersin the MLR model based on monitoring data from the Swedishnational monitoring were corrected for sea-salt inputs (eqs 1and 2), as denoted by asterisks (*).39 The water chemistryparameters used in the MLR predicting the recent (1988−2012) annual change in TOC concentration were based onannual average values for the year 2012.

* = − · − −[BC ] [BC] 1.111 [Cl ] (meq L )1(1)

* = − ·− − − −[SO ] [SO ] 0.103 [Cl ] (meq L )42

42 1

(2)

3.0. RESULTS3.1. VNIRS-TOC Model Performance and Long-Term

Reconstructions. VNIRS-TOC reconstructions were com-pared to monitoring data for model performance andevaluation. Cores were collected in 2005, thus the top 0−1.75 cm sediment is assumed to represent average conditionsbetween 2000 and 2005. The top 0−1.75 cm sedimentreconstructed VNIRS-TOC was compared to average measuredTOC between 2000 and 2005. Using a 5 year average ofmeasured TOC values compensates for annual variation inwater chemistry and differences in sedimentation rates betweenthe lakes. The resulting model had an adj. R2 of 0.74 and RMSE1.6 mg L−1 (Figure 2). There are some discrepancies in lakes

with high TOC values and this might be connected to thesmaller number of lakes with higher TOC concentrations in thecalibration set (Figure 2).29

The long-term VNIRS-TOC inferred reconstructionsshowed similar declines in lake water TOC until 1980. Well-buffered lakes in northern Sweden and lakes that received lesssulfur deposition showed a smaller absolute change inreconstructed TOC compared to weakly buffered lakes insouthern Sweden which received high sulfur deposition (Figure3).

3.2. Regional TOC Model 1860−1980 Based on VNIRS-TOC. Due to the lack of measured water chemistry for 1860−1980, the regional TOC model based on VNIRS-TOC (n =14), only used catchment characteristics and EMEP sulfurdeposition as explanatory variables to predict the temporaltrend of VNIRS-TOC between 1860 and 1980. The bestperforming MLR model used three parameters: lake area(km2), log catchment area (km2) and EMEP sulfur depositionin 1980 (mg S m−2 yr−1) (eq 3). The MLR predicted the slopeof reconstructed TOC between 1860 and 1980 with an adj. R2

0.85 and NRMSE of 12% (Figure 4).

Δ = + ·

− ·

− ·

[TOC] 0.098 0.058 [lake area]

0.069 [log catchment area]

0.000052 [sulfur 1980]

VNIRS

EMEP (3)

3.3. Regional TOC Model 1988−2012 Based on Long-Term Monitoring of Lakes. The predictive model fortemporal trends between 1988 and 2012 (eq 4) included fiveparameters related to catchment characteristics and waterchemistry. The MLR model predicted the slope of measuredTOC with an adj. R2 0.71 and NRMSE 12% (Figure 5).

Δ = − ·

+ ·

− · − ·

+ · Σ * − · *−

[TOC] 1.38 0.392 [runoff]

0.000042 [sulfur 1980]

0.0039 % wetland 0.200 [pH]

0.807 [ BC ] 1.537 [SO ]

Mon.

EMEP

42

(4)

4.0. DISCUSSIONThe simple modeling approach presented in this paper canreduce the ambiguity in reference conditions by providingcredible estimates of historical lake water TOC concentrations.This approach will be valuable for questions related to surfacewater browning, including drinking water management,9

contaminant transport40 and recovery from acidification.12

Using readily available catchment characteristics and basicwater chemical parameters, credible estimates of changes in

Figure 2. Mean annual measured TOC (2000−2005) plotted againstthe VNIRS inferred concentration from the top sediment (0.25−1.75cm). Solid line represents the 1:1 line.

Figure 3. Long-term reconstructed TOC inferred from VNIRS. All 14lakes presented here have been used in the MLR to produce theregional TOC model. The reconstructions represent the time period1860−2005. Three lakes have distinctive patterns, represented by solidlines (a) Tomeshultagolen (b) Harasjon and (c) Siggeforasjon.

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TOC from 1860 can be obtained. The VNIRS-TOCreconstructions presented in this study show similar decreasingtrends across climatic and deposition gradients until peakacidification (1980). The VNIRS-TOC reconstructions com-bined with observations from 107 monitored lakes between1988 and 2012 present an opportunity to link historical changesin TOC with present day conditions.

4.1. Estimation of TOC between 1860 and 1980 Basedon VNIRS. The VNIRS-TOC reconstructions support thehypothesis that acid deposition is a key controller of surfacewater TOC.8,20,22,41 All except for one of the reconstructedtime series showed a decrease in TOC coincident withincreases in acidic deposition before peak acidification in1980 (Figure 4). The results indicate that no change hasoccurred for this lake over the time period. The absolutechange in TOC was dependent upon catchment characteristicsand the concentration of TOC in the lake. Lakes with highTOC concentrations in southern Sweden that received highatmospheric sulfur deposition had a larger absolute change inTOC prior to peak acidification compared to low depositionand clear lakes in northern Sweden (Figure 4). Although theabsolute change might be larger in Southern Sweden, theproportional change was similar across regions.27−29 Althoughmost lakes showed a consistent VNIRS-TOC reconstruction,three lakes had a distinctive pattern, Harasjon, Siggeforasjonand Tomeshultagolen (Figure 3). The VNIRS-TOC in thesethree southern lakes had a steep decline until 1950 before peakacidification. The TOC concentration was stable during peakacidification and started increasing after the decline of sulfuremissions (Figure 3). This steep decline was captured by theparameters used in the MLR in all of the lakes (Figure 4) evenwith the distinct VNIRS-reconstruction for the lakes. Harasjonis a large, shallow (average depth of 2.3 m) nutrient-rich lakewhere wind action and autochthonous TOC productioncomplicate the interpretation of any trends. The long-termmonitoring data shows that the lake is mesotrophic, mediantotal-phosphorus 2012 was 17.5 μg L−1. Substantial changes inthe landscape18,21 in the catchments of Siggeforasjon andTomeshultagolen may have driven the early decline in VNIRS-TOC reconstructions. Siggeforasjon was lowered in 1918 andthe lake outlet was deepened and channelized during the sameperiod. Tomeshultagolen was a wetland rich catchment (22%)according to maps from the early 20th century. Historicalrecords show that most of the wetlands cover was drained for

Figure 4. Slope of individual VNIRS inferred TOC time series trends plotted against the predicted slope (mg L−1 yr−1) from the MLR until 1980.The 1:1 line is showed in the graph adj. R2 0.85 and NRMSE 12%. Three lakes with a distinctive VNIRS-TOC reconstruction (Figure 3) are markedas (a) Tomeshultagolen, (b) Harasjon and (c) Siggeforasjon.

Figure 5. Measured (filled circles) and modeled (open circles) TOCconcentration trends (mg L−1 yr−1) from the MLR based on thenational monitoring program (n = 107) plotted against measuredmean TOC concentration for the year 2010−2012 (mg L−1).Measurements for an individual lake are joined by a vertical bar.Analysis of Covariance (ANCOVA) confirmed that there was nosignificant difference between slopes for measured and predictedtrends versus measured TOC.

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more intensive forestry, today wetland cover in the catchmentis about 10%. The decrease in wetland area might have causedthe steep decline in reconstructed TOC concentration at theturn of the 20th century.In the MLR predicting the slope of VNIRS-TOC between

1860 and 1980 (eq 3), the results showed that if the lake area issmall and total catchment area is large, the possibility exists fora large change in TOC. The slope of the TOC concentrationtrend is strongly correlated with total sulfur deposition (mgm−2 yr−1) in 1980, which is consistent with the acidificationhypothesis. Using these three readily available parameters(Table 2), estimates of the historic changes in TOC for lakes inSweden and other acid sensitive areas could be obtained.It is important to keep in mind that the VNIRS-TOC

method is based on an assumption that there is no change inorganic matter quality over time. Although studies have showna change in organic matter quality associated with a recoveryfrom acidification,23,24 there are no studies showing an effect ofthese changes on reconstruction of TOC concentrations fromthe sediment record. This approach presented here is not areplacement for more resource-intensive paleolimnologicaltechniques including VNIRS-TOC reconstructions, merely acomplement and a simple approach suitable for regionalapplications and overview assessments.4.2. Estimation of TOC between 1988 and 2012 Based

on Long-Term Monitoring of Lakes. The model developedto predict the slope of TOC for 1988−2012 (eq 4) includedmore lakes (n = 107). Most lakes presented a increasing trendin TOC between 1988 and 2012. Nine alpine clear water lakesin northern Sweden with low TOC concentrations (average for2012 was 3.5 mg L−1) displayed small declining temporaltrends in TOC. These slopes were still captured in the MLR(Figure 5). The lakes with the strongest increasing trends inTOC are located in southern Sweden, with high TOCconcentrations, acid sensitive soils and high sulfur deposition(Figure 5).The model predicting temporal trends in TOC using readily

available catchment parameters and basic chemistry from 107lakes was robust (Figure 5). In comparison with the VNIRSmodel for 1860−1980, the adj. R2 and NRMSE was higher; thisis probably due to a much larger number of lakes. The lakesused to produce the MLR cover a large gradient of sea saltdeposition, from negligible contribution to almost of half of theion balance. Using sea salt corrected values of [ΣBC*] and[SO4

2−*] creates the possibility to apply the model acrossSweden, Europe and elsewhere to assess recent changes TOCtrends in lakes.The two models between 1860 and 1980 and 1988−2012

have a discontinuity between the years 1980−1988 because ofmissing monitoring data. To solve this issue, we propose thatthe slope for 1988−2012 be extrapolated to 1980 to connectthe two models.In some lake surveys TOC is not measured even though

other chemical parameters are available. Therefore, we havecreated a simple model to estimate TOC concentration in 2012(see the Supporting Information, S1). This model can be usedto anchor eqs 3 and 4 if measurements are missing. It should benoted that using this three-equation model chain willsubstantially increase uncertainty in final predicted trends.4.3. Drivers for the Change in TOC in Boreal Lakes.

Analyzing the dynamics of lake water TOC concentrations on aregional scale opens the possibility to identify potential driversin TOC from reference conditions until the present. The

VNIRS-TOC dataset exhibits similar declining trends inreconstructed TOC between reference conditions in 1860and peak acidification in 1980 (Figure 3). These decliningtrends support the hypothesis that atmospheric depositioncontrols TOC mobility in soils and surface waters during thisperiod. The deposition hypothesis states that an increase inorganic matter solubility following an increase in humiccharge42 and reduced ionic strength43 could be the mechanismbehind an increasing trend of lake water TOC concentrations.This was reflected in the model for 1988−2012 as both pH andBC*, which could function as a measure of ionic strength, weresignificant predictors of trend magnitude. This hypothesis hasalso been discussed for surface waters in the UK uplands whereorganic rich soils with low adsorption and limited competitionbetween sulfur and TOC could have amplified the solubilitycontrol on TOC.44 The MLR models show a strongrelationship between sulfur deposition and the controls ofionic strength as the driver of TOC concentration trendsduring the period of heavy acidification and subsequentrecovery. This relationship to sulfur deposition is mostapparent for lakes that had experienced a large relative changein TOC and where TOC concentrations were high duringreference conditions (Figures 4 and 5). In areas whereatmospheric deposition was low, other factors such asprecipitation, hydrology and climate might have driven thechanges in lake water TOC concentrations since referenceconditions.10,17,45−48 Present day variability in climate-relatedparameters such as temperature and precipitation will influencetemporal dynamics of lake water TOC concentrations49 andshould be investigated further. Since acid deposition is likely toremain low relative to historical levels, a warming climate isexpected to be the main driver for future changes in lake waterTOC concentrations.16,50,51 However, at the present time, nosingle unifying climate-related mechanism has been proposed asa controller of surface water TOC concentrations. Multipleclimatic factors including warmer temperature, runoff andchanging in the timing and amount of precipitation can affectthe fluxes and concentrations of TOC in lakes and streams.48

For instance, longer drought periods driven by climate changemight decrease the organic carbon export to streams.48

Increased runoff4 and summer precipitation17 have beenidentified as factors that can increase TOC export.52 Increasedprecipitation is likely to increase the groundwater table to levelsthat it comes into contact with soils with higher organic mattercontent and thus the export of TOC will increase. Increasedterrestrial vegetation cover associated with a warmer climatemay lead to substantial increases in TOC concentrations in thefuture.16 Interannual variability of DOC export can becontrolled by individual events at regional53 and watershedscales.54

It has been suggested that TOC concentrations will continueto increase until they return to reference condition levels.8 Theresults presented here (Figure 6) suggest that TOCconcentrations in Swedish lakes are similar to those duringreference conditions. If TOC concentrations will not increaseabove reference condition values, the concentration of TOC inSwedish surface waters is not likely to increase substantially inthe future. Based on VNIRS-TOC reconstruction and anindependent validation dataset, it can be seen that surface waterTOC concentrations have recovered back to referencecondition levels just in a few decades (Figure 6). The recoveryof TOC to reference condition levels is an anomaly comparedto other water chemistry parameters that were affected by

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acidification and have not yet fully recovered including pH,ANC and BC in acid-sensitive Swedish lakes.55 Further work isneeded to see if surface water TOC concentrations havereturned to reference condition values in other regions thathave experienced increases in surface water TOC over the lastthree decades. These results provide valuable information forfuture surface water management in Sweden and elsewhere.Any future changes in TOC are likely to be driven by factorssuch as climate, land use or land management as the lakes haverecovered from the effects of acidification. This is an importantfinding for regions dependent on surface water raw watersources as there has been a great deal of discussion regardingthe potential impact of increasing TOC concentrations ondrinking water treatability and quality.9

4.4. Policy Implications and Water Management. Theimplementation of European Union Water FrameworkDirective (WFD)56 and similar directive such as U.S. CleanWater Act promote the use of reference conditions and theundisturbed state as overall goals for water management.Different methods have been used to identify acidification-related reference conditions including geochemical modeling3

diatom reconstructions57 and historical biological data.58 Ingeneral, the different methods of estimating referenceconditions exhibit good agreement on a regional scale butmight deviate substantially on local levels water bodies.58 Oneof the main issues discussed in acidification research during thepast decade is the need to account for temporal changes inTOC concentrations when estimating reference conditionpH.4,59,60 It has been shown that estimation of referencecondition pH is strongly dependent on the TOC concentrationused.4 This has significant policy-related implications forcountries such as Sweden where acidification status is definedas the difference between reference condition and current pH.61

The models we present for estimating reference conditionTOC are important for two reasons. (i) Unlike previous studiesthat have focused on measured water chemistry, the workpresented here uses estimates of reference conditions obtainedfrom the sediment record. Although the VNIRS method hasbeen applied previously, it is time-consuming and impracticalfor water management in a country like Sweden with over 100000 lakes. However, the simple model developed here can be

used when a regional assessment of historical TOC is needed.With these simple models, new insights on environmentaldrivers of surface water TOC concentrations can be obtainedfor drinking water management and other purposes. (ii) Thepossibility to estimate historical TOC concentrations is criticalfor assessing WFD ecological status, which is defined based ondeviation from reference conditions. The simple estimators ofreference condition TOC presented here can reduce thepredictive uncertainties and increase credibility of referencecondition estimates generated by more complex process-basedgeochemical models.

■ ASSOCIATED CONTENT*S Supporting InformationModel to estimate the TOC concentration in the year 2012 ifmeasurements of TOC are missing in the specific survey;evaluation and description is given (S1 and Figure S1). Thismaterial is available free of charge via the Internet at http://pubs.acs.org.

■ AUTHOR INFORMATIONCorresponding Author*S. Valinia. E-mail: salar.valinia@slu. Phone: +46 73 50 15 849.Fax: +46 18 67 31 56.NotesThe authors declare no competing financial interest.

■ ACKNOWLEDGMENTSWe thank three anonymous reviewers whose commentsimproved the quality of the paper. We thank Jose Ledesmafor valuable discussions. Salar Valinia was funded by Knut andAlice Wallenberg Foundation for a research visit at CEH,Bangor, U.K. Martyn Futter was funded by the MISTRAFutureForests program, Norwegian Council ECCO project andNordForsk DomQua.

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Figure 6. VNIRS-inferred reference value (open circles mg L−1) andmodeled reference values (filled circles) plotted against three yearaverage of measured TOC for 2010−2012. The 1:1 line is shown inthe graph.

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